Triple
T2810993
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sean McVay |
E54168
|
entity |
| Predicate | collegePositionPlayed |
P7105
|
FINISHED |
| Object | wide receiver |
—
|
LITERAL FINISHED |
How this triple was built (2 steps)
Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.
NER
Named-entity recognition
gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: wide receiver | Statement: [Sean McVay, collegePositionPlayed, wide receiver]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: collegePositionPlayed Context triple: [Sean McVay, collegePositionPlayed, wide receiver]
-
A.
positionPlayedInCollege
chosen
Indicates the specific playing position an individual held on a sports team during their college career.
-
B.
collegePosition
Indicates the role, title, or position an individual holds within a college or university.
-
C.
playedCollegeSport
Indicates that the subject participated in an organized college-level sport for the object institution.
-
D.
playedCollegeTeam
Indicates that an athlete was a member of and competed for a particular college sports team.
-
E.
playsInPosition
Indicates that an entity (typically a player) performs or operates in a specific role or position within a game, sport, or activity.
- F. None of above.
Provenance (3 batches)
The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.
| Step | Stage | Batch ID | Status | When |
|---|---|---|---|---|
| creating | Elicitation | batch_69ab49dcee188190b5c6eca9ae9e3469 |
completed | March 6, 2026, 9:40 p.m. |
| NER | Named-entity recognition | batch_69abde335b38819090c70d5e2ca14d79 |
completed | March 7, 2026, 8:13 a.m. |
| PD | Predicate disambiguation | batch_69abdd0740208190911dc9c9546a79ae |
completed | March 7, 2026, 8:08 a.m. |
Created at: March 6, 2026, 9:59 p.m.